Obesity prevalence in youth with spina bifida (SB) is reported as high as 74%, dramatically higher than their typically developing (TD) peers at 16.9%. Obesity is associated with life-long medical, psychological and economic burdens. In SB, obesity further limits one?s independence and ability to self-manage health as well as places them at risk for secondary obesity-related comorbidities. Accurate measurement of body fat is critical as higher levels are associated with increased health risks. Once body fat is established, knowledge of the individual?s total daily energy expenditure (TDEE) is essential to determine an individual?s recommended daily caloric intake needed to maintain or change body weight. Successful identification, prevention and/or treatment of obesity is severely compromised by the lack of: 1) a clinically feasible, cost-effective and valid method to measure body fat, and 2) data on TDEE of youth with SB. Inherent characteristics of SB complicate the ability to accurately measure height, to identify body fat and are associated with a decreased energy expenditure. In addition, a Body Mass Index (BMI), commonly used in clinics as a surrogate estimate of body fat to screen for obesity is inaccurate when used in SB. Proposals for alternative measures or methods to accurately identify body fat in individuals with SB have been made, but have yet to be tested in a sufficiently large sample. To address these gaps, we will develop two independent methods and/or algorithms for use in youth with SB, one to model body fat in a clinic environment and one to predict TDEE in order to determine daily caloric intake recommendations. This multisite, cross-sectional study will include 232 youth with SB, ages 5-18 (stratified by age and mobility status). Sites include four pediatric SB programs from different geographical regions. Participants will have four body composition measures (waist circumference, four-site skinfolds, bioelectrical impedance analysis, and Doubly Labeled Water [DLW]) and up to five height measures (standing [if able to stand independently], arm span, recumbent, knee height and ulnar length) performed. DLW analysis and calculations will provide the criterion body fat%, fat-free mass and TDEE. The body composition and/or height measures will be used to develop an algorithm that accurately models body fat% and categorizes weight status of youth with SB. Based on the average TDEE, an algorithm will be developed to predict energy requirements with a best-fit model based on fat-free mass, sex, age, ambulation status height and/or weight. In addition, a nutrition and physical activity screener will be employed to describe the dietary intake and patterns of physical activity in youth with SB. The proposed study aligns with the mission and research goals of NICHD by ensuring that all children have the opportunity for healthy and productive lives by optimizing independence and promoting the health of populations at an increased risk for obesity by generating findings to be used in the creation and testing of weight management interventions.